This invention relates to color magnetic resonance imaging.
In traditional magnetic resonance imaging (MRI), a patient lies within a tubular structure where the patent is subjected to spatial and temporal magnetic field gradients. MRI uses the fact that atomic nuclei spin to collect image data. If the number of protons in a nucleus is even, their spins will cancel; however, if there is an odd number, there will be a net spin that can be used to conduct MRI, see, e.g., U.S. Pat. No. 5,397,987, which is incorporated by reference herein. Hydrogen nuclei have a single proton, and many MRI techniques utilize hydrogen nuclei since they are pervasive in human tissue. When a subject is placed in a main magnetic field, its nuclei align in the direction of the field (i.e., along the xe2x80x9cmagnetization axisxe2x80x9d); the orientation of the nuclei can be represented by a magnetization vector, see, e.g., Horowitz, MRI Physics for Radiologists: A Visual Approach, 1995, which is incorporated by reference herein. These spinning nuclei can precess in a conical manner around the magnetization axis, generally out-of-phase with respect to each other. To induce in-phase spinning at the resonance frequency of particular nuclei, a radio frequency (RF) excitation pulse is broadcast at that resonance frequency. This RF pulse also causes the nuclei to rotate with respect to the magnetization vector created by the main magnetic field, see, e.g., Horowitz, MRI Physics for Radiologists: A Visual Approach, 1995, incorporated by reference herein. After the RF excitation pulse, free induction decay (FID) signals are collected and used to generate MR images.
There are two major forms of relaxation, or decay, in MRI: a longitudinal component and a transverse component, see, e.g., E. Fukushima and S. Roeder, Experimental Pulse NMRxe2x80x94A Nuts and Bolts Approach, 1981, incorporated herein by reference. One form of relaxation is xe2x80x9cde-phasingxe2x80x9d of the nuclear spins over time after the RF pulse. This phenomenon is known as the xe2x80x9ctransverse relaxationxe2x80x9d (or spin-spin relaxation), and the time constant for this relaxation is labeled T2. The other form of relaxation is the realignment of the magnetization vectors along the main magnetic field. This is known as the xe2x80x9clongitudinal relaxationxe2x80x9d (or spin-lattice relaxation), and the time constant for this relaxation is labeled T1. Both of these relaxation phenomena are characterized by exponential decay.
MR images are generated from the FID signals. These images are often in black and white. Techniques are also known for producing gray scale images using T1, T2, and proton density data, see, e.g., Ronald T. Droege et al., xe2x80x9cNuclear Magnetic Resonance: A Gray Scale Model for Head Images,xe2x80x9d Radiology, 148:763-771 (1983). There are also methods for generating color images. One approach is to convert a monochrome image into one that is in color, see U.S. Pat. No. 4,998,165. Other approaches to producing color images take both T1 and T2 data as inputs and use specified methods to render color images, see, e.g., U.S. Pat. Nos. 5,486,763; 5,410,250; 4,789,831.
In one aspect of the invention, an article containing a computer-readable medium on which a computer program is stored has instructions for causing a processor to receive spatial magnetic resonance data obtained from a sample and generate color image data using the magnetic resonance data. The color image data reflect both a magnetic resonance property of the magnetic resonance data and a function of the magnetic resonance property. This invention permits a user to evaluate the magnetic resonance property of the sample to ascertain the spatial composition of the sample.
Embodiments of this aspect of the invention include one or more of the following features. The function can be selected to enhance the color image data. This enhancement is the result of providing greater informational content. For example, the function of the magnetic resonance property can enhance the color image by indicating the confidence level of the magnetic resonance property. The function can be selected to enhance at least one region of a color image produced from the color image data. This region is enhanced on the basis of hue, brightness, or saturation. By using hue, brightness, or saturation to enhance the color image by indicating, e.g., the confidence level of a magnetic resonance property, the color image facilitates quick and easily comprehension of this information by a researcher or clinician. The function can also be selected to distinguish at least one region of the color image on the basis of the composition of the material in the corresponding region of the sample. This is useful, e.g., to identify regions where a probe passes through tissue in a sample. In addition, the function can be selected to distinguish at least one region of the color image on the basis of the presence of material in the corresponding region of the sample. The function can be further selected to distinguish at least one region of the color image on the basis of the homogeneity of material in the corresponding region of the sample. Distinguishing on the basis of the homogeneity of material in a region of the sample permits a user of the color image to differentiate between regions containing homogenous tissue and regions containing a mixture of tissue.
The magnetic resonance data are obtained using a Fourier transform of free induction decay signals. The magnetic resonance property can be an estimate of T2, T1, or thermal relaxation. By using a single parameter, this technique exploits the particular advantages of that magnetic resonance property, such as the sensitivity T2 to time-dependent changes. Since T2 is affected by metabolic changes in the brain, T2 can be used for functional MRI, e.g., to track changes over time, through treatment regimens, between or among subjects, or a combination thereof. For example, this approach can be used to monitor levels of drugs or other chemicals in the blood or other tissues over time. The estimate of T2, {circumflex over (T)}2, is calculated using:                               T          ^                2            =                        σ          t          2                          C                      x            ,            t                                ,    where                      σ        t            =                                    N                          -              1                                ⁢                                    ∑                              n                =                0                                            N                -                1                                      ⁢                          xe2x80x83                        ⁢                          t              n              2                                      -                              (                                          N                                  -                  1                                            ⁢                                                ∑                                      n                    =                    0                                                        N                    -                    1                                                  ⁢                                  xe2x80x83                                ⁢                                  t                  n                                                      )                    2                      ,          
        ⁢                  I        N            =                                    N                          -              1                                ⁢                                    ∑                              n                =                0                                            N                -                1                                      ⁢                          xe2x80x83                        ⁢                          x              n                                      -                                            N                              -                1                                      ⁢                                          ∑                                  n                  =                  0                                                  N                  -                  1                                            ⁢                              xe2x80x83                            ⁢                              t                n                                                                        T              ^                        2                                ,  
and where N is a number of echo times, tn, and xn=ln(yn) for yn greater than 0; otherwise, xn=xe2x88x921, and where yn is an intensity of a signal at an echo time, tn. Using specially chosen echo times, direct values of signal intensity, yn, rather than their natural logarithms, can be used for xn, and a value other than xe2x88x921 could be used for negative yn.
The function of the magnetic resonance property can be a function of fit of the T2 data to a reference curve. Including this characteristic of the T2 data in the color image allows a viewer to distinguish between a voxel with a single type of tissue with a particular T2 and a voxel with different tissues that together yield that T2. This fit, E, can be calculated using:       E    =                            (                                    σ              x              2                        -                                          C                                  x                  ,                  t                                            /                                                T                  ^                                2                                              )                          1          /          2                            I        N              ,
and the following additional relationships,             σ      x        =                            N                      -            1                          ⁢                              ∑                          n              =              0                                      N              -              1                                ⁢                      xe2x80x83                    ⁢                      x            n            2                              -                        (                                    N                              -                1                                      ⁢                                          ∑                                  n                  =                  0                                                  N                  -                  1                                            ⁢                              xe2x80x83                            ⁢                              x                n                                              )                2              ,      
    ⁢            C              x        ,        t              =                            N                      -            1                          ⁢                              ∑                          n              =              0                                      N              -              1                                ⁢                      xe2x80x83                    ⁢                                    x              n                        ⁢                          t              n                                          -                        (                                    N                              -                1                                      ⁢                                          ∑                                  n                  =                  0                                                  N                  -                  1                                            ⁢                              xe2x80x83                            ⁢                              x                n                                              )                ⁢                              (                                          N                                  -                  1                                            ⁢                                                ∑                                      n                    =                    0                                                        N                    -                    1                                                  ⁢                                  xe2x80x83                                ⁢                                  t                  n                                                      )                    .                    
The function can also be a function of intensity. Display of intensity information permits one to distinguish readily between voxels containing mostly air and those containing tissue. The intensity, IN, can be calculated using:       I    N    =                    N                  -          1                    ⁢                        ∑                      n            =            0                                N            -            1                          ⁢                  xe2x80x83                ⁢                  x          n                      -                                        N                          -              1                                ⁢                                    ∑                              n                =                0                                            N                -                1                                      ⁢                          xe2x80x83                        ⁢                          t              n                                                            T            ^                    2                    .      
The instructions can include both a function of fit of the first data to a reference curve and a function of intensity. The preceeding equations can be used to calculate them, or a threshold measure can be used to eliminate a pre-determined range of values. This provides the user with the useful information provided by both characteristics of the T2 data. The estimate of T2, the fit of the first data to the reference curve, and the intensity are used to calculate hue, saturation, and brightness. Using these three parameters, the color images provide a greater depth of information than available in grayscale images. The hue, H; saturation, S; and brightness, V, are calculated using:
H=[1+({circumflex over (T)}2/T0)2]xe2x88x921/2,
S=0 for Exe2x89xa7xc2xd,S=1xe2x88x922E for xc2xd less than E less than 0, and S=1 for Exe2x89xa60, and
V=0 for INxe2x89xa60,V=IN/8 for 0 less than IN less than 8, and V=1 for INxe2x89xa78,
where T0 is a constant. In this intuitive approach, bright colors represents high intensity and dim colors represent weak intensity. These equations can be tweaked to enhance the color display depending on the range of values obtained for the estimates of T2, goodness-of-fit, and intensity.
The color image data are in RGB format. This renders the data suitable for convenient display on computer monitors and storage in cross-platform image files (e.g., JPEG, TIFF, PPM files). The individual color values in the color image data are given by:
R=MV[1+S cos(xcex8)],
G=MV[1+S cos(xcex8xe2x88x92xcfx86)],
B=MV[1+S cos(xcex8+xcfx86)], using the following additional relationship,       M    =                  (                              2            b                    -          1                )            c        ,
wherein b is the number of bits per voxel and c is the number of colors. These equations can be adjusted to enhance the user""s ability to distinguish between different types of tissues, e.g., white and gray matter in the human brain. The images can also be used to ascertain the porosity of T2 data or investigate samples described by the Arrhenius equation.
In another aspect, the invention includes a method of color imaging that involves receiving spatial magnetic resonance data obtained from a sample and generating color image data using the magnetic resonance data. The color image data reflect both a magnetic resonance property of the magnetic resonance data and a function of the magnetic resonance property.
Yet another aspect involves a color imaging system that has a magnetic resonance scanner, a receiver, and a processor. The processor receives spatial magnetic resonance data obtained from a sample and generates color image data using the magnetic resonance data. The color image data reflect a magnetic resonance property of the magnetic resonance data and a function of the magnetic resonance property.
Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.